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Record W2737883449

A Perturbation-inspired Method of Generating Exact Solutions in General Relativity

2010· dissertation· en· W2737883449 on OpenAlexfundno aff
Brian Wilson

Bibliographic record

VenueTSpace (University of Toronto) · 2010
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicRelativity and Gravitational Theory
Canadian institutionsnot available
FundersUniversity of TorontoGovernment of Ontario
KeywordsTheory of relativityTheoretical physicsApplied mathematicsCalculus (dental)MathematicsComputer sciencePhysicsMedicine
DOInot available

Abstract

fetched live from OpenAlex

General relativity has a small number of known, exact solutions which model
\nastronomically relevant systems. These models are highly idealized situations.
\nEither perturbation theory or numerical simulations are typically needed to
\nproduce more realistic models. Numerical simulations are time-consuming and
\nsuffer from a difficulty in interpreting the results. In addition, global
\nproperties of numerical solutions are nearly impossible to uncover. On the 
\nother hand, standard perturbation methods are very difficult to implement
\nbeyond the second order, which means they barely scratch the surface of
\nnon-linear phenomena which distinguishes general relativity from Newtonian gravity. 
\n
\nThis work 
\ndevelops a method of finding exact solutions, inspired by perturbation
\ntheory, 
\nwhich have energy-momentum tensor components that approximately satisfy
\ndesired relationships. We find a spherical lump of matter
\nwhich has a density profile $\\mu \\propto r^{-2}$ in a Robertson-Walker
\nbackground; it looks like a galaxy in an expanding universe. 
\nWe also find a plane-symmetric perturbation of 
\na Bianchi type I metric with a density profile $\\mu \\propto z^{-2}$; it
\nmodels a jet impacting a sheet-like structure.
\nThe former solution involves a wormhole while the latter involves a 
\ntwo dimensional singularity. These are both non-linear structures which
\nperturbation theory can never produce.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.277
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

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